System and method for multivariate testing of messages to subgroup in a one-to-many messaging platform

ABSTRACT

A system and method for multivariate testing of messages to a subgroup in a one-to-many messaging platform. A client text message is generated for transmission to a number of users via one or more messaging services. A subset of users is defined according to one or more attributes of the text message or the users, and the client text message is transmitted only to users in the subgroup. The transmission is analyzed for performance metrics, such as actions or reactions by users in the subgroup, and based on the performance metrics, the message is optimized for transmission to the larger group of users. Optimization happens rapidly.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims the benefit of priority of U.S.Provisional Application No. 62/800,403 filed on Feb. 1, 2019; andentitled “One to Many Messaging Platform,” the entirety of which ishereby incorporated by reference herein.

TECHNICAL FIELD

The subject matter described herein relates to an electronic messagingplatform, and more particularly to a system and method for groupingresponses in a one-to-many messaging platform for exchanging messagesbetween a client (such as an influencer, celebrity, company or the like)and users (such as fans of the client).

BACKGROUND OF THE INVENTION

Electronic messaging exists in many different forms, and typicallyoccurs over a wireless communication channel between computing devices,which are often mobile computing devices such as smart phones, laptopcomputers, or tablet computers. Electronic messages can take the form oftext, graphic (such as an image, video, or other graphic such as an“emoji.” There are many different electronic messaging protocols, suchas Short Messaging Service (SMS), which is often limited only to shorttext messages, and Multimedia Messages (MMS), which can contain digitalimages, videos, audio content, and ideograms such as emojis, GIFs, orthe like. etc.

There also exists various application platforms for exchangingelectronic messages. Most commonly, electronic messages are sent andreceived over a wireless cellular network based on a user's long-codephone number, i.e. in the U.S., the three-digit area code plusseven-digit mobile phone number that is assigned to a user by a carrierthat controls the wireless or cellular network and manages any trafficon such network.

While most messaging is performed peer-to-peer (P2P) or even in smallgroups, one-to-many communication of messaging at a massive scale, i.e.a “social media” type application having more than just a handful ofmessage recipients, is technically difficult and challenging. Other thansocial media applications and platforms such as Facebook®, Twitter®,Instagram®, and others, large-scale communication of messages betweenclients (also referred to herein as “influencers,” “celebrities,” or thelike) and associated users (also referred to herein as “fans,”“audience,” “followers,” or the like) is limited by the wirelessnetworks and the carriers that manage them, and by the technologiesthemselves. However, engagement rates, which define how engaged a usermight be to interacting with, following, or communicating with a client,over text messaging far surpass the engagement rates on social mediaplatforms mentioned above. Yet still, at large scale, clients have adifficult time managing and keeping up with the large numbers ofmessages, both transmitted and received. Audience platforms and audiencetargeting exist, but have not been done for text messaging platformsbecause one-to-many communication has previously not been possible atlarge scale.

For instance, there currently exists no platform that allows devicesassociated with long-code phone numbers to send a large volume ofmessages. No current social media platform allows users to connect withclients over text messaging, particularly using such long-code phonenumbers, nor allows clients to engage directly with their users withoutintermediation by a social media platform.

What is needed is a messaging platform that provides flighting (i.e.transmission over one or more communication networks) of one-to-manytext messages (both text and content-rich messages), and which performsmultivariate testing of messages before they are send out broadly to theentire target audience. Also needed is a platform that gives clientstools that are needed to manage the incoming volume of messages throughgrouping and aggregating, and by application of machine learning andartificial intelligence algorithms that augment a client's naturalmessaging style and tone. Finally, such a platform needs recommendationsand authoring assistance for text message communications.

BRIEF SUMMARY OF THE INVENTION

This document describes a messaging platform, system and method thatprovides for one-to-many (and many-to-one) message transmission over oneor more communication networks). The messages can be text and/orcontent-rich messages, and the communication networks can be a wirelessnetwork that is managed and controlled by one of the various wirelesscommunication carriers. In some implementations, a system and methoddescribed herein performs multivariate testing of messages before theyare transmitted to a target audience. The multivariate testing caninclude analytics to ascertain whether a message is contextuallyappropriate, based on a current environment, audience base, topic, orthe like. The systems and methods provide tools to manage a large volumeof incoming and outgoing messages, through grouping and aggregating, andby application of machine learning and artificial intelligencealgorithms that augment a client's natural messaging style and tone, aswell as provide a recommendations and authoring engine for increasingresponsiveness and communication between clients and their users.

In some aspects, a method and system are described for groupingresponses in a one-to-many messaging platform are described. In certainaspects, a method includes the steps of receiving, by a messagingplatform, a plurality of response text messages from a correspondingplurality of users in response to a first text message from a client,the first text message being transmitted via one or more messagingservices that interface with the messaging platform. The method furtherincludes analyzing, by a computer processor associated with themessaging platform and according to executable instructions, one or moreattributes associated with each of the plurality of response textmessages. The method further includes generating, by the computerprocessor, metadata for each of the plurality of response text messages,the metadata representing the one or more attributes associated witheach of the plurality of response text messages or a user associatedwith selected ones of each of the plurality of response text messages.The method further includes storing, by the computer processor, themetadata for each of the plurality of response text messages in adatabase, the storing further including linking the metadata with thecontent of each of the plurality of response text messages.

In some other aspects, a method and system for determining sentimentand/or semantics of responses in a one-to-many message platform aredescribed. In one aspect, a method includes communicating, via one ormore messaging services that interface with a messaging platform, one ormore text messages between a client and a plurality of users. The methodfurther includes receiving, by the messaging platform via the one ormore messaging services, user text messages from individual ones of theplurality of users. The method further includes executing, by a machinelearning module of the messaging platform, one or more artificialintelligence algorithms on the received user text messages, andprocessing, according to the artificial intelligence algorithms of themachine learning module. The method further includes generating, basedon one or more of variables associated with the processed user textmessages, metadata for each of the user text messages, the metadatarepresenting one or more attributes associated with content of each ofthe plurality of user text messages or a user associated with the usertext messages.

In some other aspects, a method and system for segmenting users of aone-to-many messaging platform are described. In certain aspects, amethod includes receiving, by a messaging platform, a first text messagefrom a client via a first messaging service that interfaces with themessaging platform, the first text message being configured fortransmission via one or more second messaging services to user devicescorresponding with a plurality of users, each of the plurality of usersbeing registered with the messaging platform and associated with theclient via the messaging platform. The method further includessegmenting, by the messaging platform, the plurality of users accordingto one or more user segments, each of the one or more user segmentsbeing based on one or more user attributes associated with the pluralityof users, the one or more attributes being defined by static metadatathat is generated when each user is registered with the messagingplatform, and by dynamic information about user behavior using themessaging platform and/or the one or more second messaging services. Themethod further includes customizing, by the messaging platform, thefirst text message into a set of one or more second text messagesaccording to the segmenting, the customizing providing a context to eachof the set of second text messages, the context corresponding to the oneor more user attributes. The method further includes transmitting, bythe messaging platform via the one or more second messaging services,the set of second text messages to the user devices associated with eachof at least some of the plurality of users.

In some other aspects, a method and system for multivariate testing ofmessages to a subgroup in a one-to-many messaging platform aredescribed. In certain aspects, a method includes generating, by amessaging platform, a text message associated with a client, the messagebeing generated for transmission to a plurality of users via one or moremessaging services, and defining, by the messaging platform, a subset ofthe plurality of users, the subset being defined according to one ormore attributes associated with the text message and/or the plurality ofusers. The method further includes transmitting, by the messagingplatform and via at least one of the one or more messaging services, thetext message to the subset of the plurality of users. The method furtherincludes analyzing, by the messaging platform, one or more variables ofthe transmitting of the text message to the subset of the plurality ofusers, the analyzing generating performance metrics of the text messagerelative to the subset of the plurality of users. The method furtherincludes optimizing, by the messaging platform, the text message basedon the performance metrics generated from the analyzing, andconfiguring, by the messaging platform, the optimized text message fortransmission to the plurality of users or other subsets of the pluralityof users via the one or more messaging services.

Implementations of the current subject matter can include, but are notlimited to, methods consistent with the descriptions provided herein aswell as articles that comprise a tangibly embodied machine-readablemedium operable to cause one or more machines (e.g., computers, etc.) toresult in operations implementing one or more of the described features.Similarly, computer systems are also described that may include one ormore processors and one or more memories coupled to the one or moreprocessors. A memory, which can include a non-transitorycomputer-readable or machine-readable storage medium, may include,encode, store, or the like one or more programs that cause one or moreprocessors to perform one or more of the operations described herein.Computer implemented methods consistent with one or more implementationsof the current subject matter can be implemented by one or more dataprocessors residing in a single computing system or multiple computingsystems. Such multiple computing systems can be connected and canexchange data and/or commands or other instructions or the like via oneor more connections, including but not limited to a connection over anetwork (e.g. the Internet, a wireless wide area network, a local areanetwork, a wide area network, a wired network, or the like), via adirect connection between one or more of the multiple computing systems,etc.

The details of one or more variations of the subject matter describedherein are set forth in the accompanying drawings and the descriptionbelow. Other features and advantages of the subject matter describedherein will be apparent from the description and drawings, and from theclaims. While certain features of the currently disclosed subject matterare described for illustrative purposes in relation to a messagingplatform, it should be readily understood that such features are notintended to be limiting. The claims that follow this disclosure areintended to define the scope of the protected subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, show certain aspects of the subject matterdisclosed herein and, together with the description, help explain someof the principles associated with the disclosed implementations. In thedrawings,

FIG. 1 illustrates a one-to-many messaging platform;

FIG. 2 illustrates a messaging architecture for a one-to-many messagingplatform; and

FIG. 3 depicts a client user interface and dashboard in accordance withimplementations described herein;

FIG. 4 depicts a client mobile device user interface in accordance withimplementations described herein;

FIG. 5 depicts a client user interface and dashboard in accordance withimplementations described herein;

FIG. 6 is a flowchart of a method for grouping responses in aone-to-many messaging platform;

FIG. 7 is a flowchart of a method for determining sentiment and/orsemantics of responses in a one-to-many messaging platform;

FIG. 8 is a flowchart of a method for segmenting users of a one-to-manymessaging platform; and

FIG. 9 is a flowchart of a method for multivariate testing of messagesto a subgroup in a one-to-many messaging platform.

When practical, similar reference numbers denote similar structures,features, or elements.

DETAILED DESCRIPTION OF THE INVENTION

One-to-Many Communication Over Text at Massive Scale

In accordance with some implementations of the subject matter describedherein, a Software-as-a-Service (SaaS) platform is provided whichfacilitates one-to-many communication over text messaging at massivescale. FIG. 1 illustrates a system 100 for managing inbound and outboundmessages at large to massive scale, from individual ones of clients toseveral and up to many millions of users. The system 100 includes amessaging platform 102 for processing, storing and executing variousautomated functions on messages exchanged between a client device 101,such as mobile phone, tablet computer, laptop computer, desktopcomputer, or the like, and a number of user devices 103, also such asmobile phone, tablet computer, laptop computer, desktop computer, or thelike. Each of the client device 101 and user devices 103 includecommunication modules such as a transceiver or radio for communicatingmessages wirelessly over one or more messaging services 104, such as isprovided by a wireless carrier, an application provider, or otherservice provider.

The messaging platform 102 of the system 100 includes one or moreprocessing modules 106 that execute instruction from non-transitorymachine-readable media 106, or which include a hard-wired processor suchas an application-specific integrated circuit (ASIC), a reprogrammableor reconfigurable processor such as a field-programmable gate array(FPGA), or other computer processor. The one or more processing modules106 process user and client data, as well as inbound and outboundmessages (in both directions), for aspects such as sentiment, content,semantics, mood, receptiveness, or the like, and which are furtherdescribed below. The messaging platform 102 further includes one or moredatastores 110, which can include one or more of a relational database,a non-relational database, a database cluster of distributed databasenodes, and/or cloud storage. Each datastore 110 includes both hardwareand software to execute data storage, organization, and retrievalfunctions.

As in one example, a large number of users can text their favoriteclients just as easily as they would text a friend or family member.Clients of the platform can capture, segment, and reach millions ofusers using a communication channel that provides unparalleledengagement rates. Clients can send videos, images, text and/or emojisdirectly with each individual user of their audience in one-to-onedirect messages, or send broadcasts of messages to their entire audienceat thousands of messages per second, without being filtered or otherwiselimited by SMS carriers. Clients can reach their users directly andbuild audience identity and targeting data directly, without dependingon social media platforms who hoard this information from the client.Clients can do this using an actual, durable long-code phone number sothat users can store the client in their address book or contact list intheir user device 103.

Accordingly, each user can use the system as if they have a directconnection to a client. In some implementations, the system employsintelligence in the form of machine learning or artificial intelligenceto help clients and their users who to engage with, and when. The systemprovides scalability, so that each client can understand and interactpersonally with millions of users, as augmented by the system to assistthe client in generating realistic messages that arecontextually-relevant and even user-specific.

In some implementations, the system generates a unique long-codetelephone number for each client. The system collects data from eachuser who sends a message to the client according to the assigned uniquelong-code telephone number and via any of a number of communicationchannels or messaging services thereon. The system monitors activity,location, and purchases by users to provide clients intelligentsuggestions on who to message. These targeted messages can becontextually-aware and relevant to the messaging content, as well asuser preferences and engagement levels.

In preferred implementations, the system includes a client dashboard.The dashboard can be formatted for a desktop or laptop computergraphical user interface (GUI), or for a user interface (UI) of a mobiledevice such as a mobile smart phone or tablet computer. The dashboardcan be generated by a computer program or application, and can beintegrated or connected with an analytics engine and/or performance andmonitoring engine.

The system can include one or more application programming interfaces(APIs) for interfacing with, without limitation, a cloud communicationplatform such as Twilio®, and a computing resource manager such asApache Mesos®. The system includes a data management platform (DMP) thatstores all the information about the audience of each client. The DMPcan be a multi-tenant database to segregate the data based on client,and can protect the data by any number of data protection measures. Forinstance, user (audience) data can be secured so as to not be shared oraccessed by third party data processing systems, which is a major flawof conventional social networking platforms.

The system can be configured to perform grouping and aggregating.Messages particularly from users, can be grouped and/or aggregated byarea code, city, age, state, sex. In some implementations, messages canbe grouped by content aware grouping, using AI, Natural Languageprocessing, etc. for creating topics and/or conversations. In thismanner, if a conversation is defined for a group of messages, they canbe aggregated by conversation to involve multiple clients and all ofeach of the clients' users.

The dashboard provides message sorting of inbound messages based on anyof a number of variables or settings, such as keywords, contextualanalysis, user demographics, or the like. The dashboard also allowsclient to manage their messaging activity with their users byaggregating, segregating, filtering, testing, or processing messagesaccording to any number of variables, such as user demographics, numberof messages, local time zones, message content, or the like.

Flighting of One-to-Many Text Messages

When sending a message to a large audience, first send variations of themessage to smaller sample sets and measure the performance of eachvariation against target metrics. The system automatically performsanalytics on the metrics for statistical significance and hitting goals,and allows the sender to send the best variation of a message to theentire audience, or to send different variations to different largesubsets based on audience targeting/demographics. Through multivariatetesting, a feedback loop is created that enables optimization of themessages over time, against key performance metrics.

For example, the system can generate and enable transmission of “trialballoon” messages to select users, and which are configured to test userreceptiveness.

Recommendations and Authoring Assistance for Text Message Communications

When sending a message to a large audience and getting large numbers ofreplies, prioritize and group the replies so that the sender can focuson the ones that matter, and can send additional broadcast messages toresponders grouped by similar replies or other common characteristics.Automatically generate groupings based on analysis of reply content, andautomatically generate suggested replies to those groups. Automaticallyprioritize these conversations for the sender. In any one-to-manycommunication system, the large numbers of replies are impossible tomanage on a one-to-one basis and need to be grouped and replied to inbatches. Software-assisted grouping, along with the other featureslisted above, enable senders to effectively maintain two-waycommunication with large numbers of recipients.

The system can include one or more processing modules for executingvarious functions. FIG. 2 illustrates a messaging platform 200 thatprovides an event bus and message broker 202. The event bus and messagebroker 202 processes, queues and manages inbound and outbound messagesthat are transmitted via one or more messaging services provided byintercarrier vendors. In some implementations, the event bus and messagebroker can use advanced message queuing protocol (AMQP) or the like. Theevent bus and message broker 202 includes an inbound messages module 204for managing messages received from one or more of the intercarriervendors 201 via a user messages processor module 206, which can includea message service handler (MSH) or message gateway, such as Hermes® orthe like.

User messages inbound from the intercarrier vendors 201 are checkedagainst user registration data in a user registration datastore 208 forexisting, registered users, and then queued for being processed by theinbound messages module 204 of the event bus and message broker 202. Anymessages received from a non-registered user are queued in a userregistration module 210 for onboarding the user, where user informationsuch as demographic data, phone number, behavioral information, or thelike, is stored in a user detail datastore 212. At least some of theinbound messages received by the inbound messages module 204 are sent tomessage processor, which processes the messages with one or moreartificial intelligence algorithms or machine learning for executingfunctions such as, without limitation, determining semantics, sentimentsand or mood, user engagement, or the like. Processed messages are sentto an inbound processed message module 216 for functions such asfiltering, grouping (both by user, such as age, gender, city, or thelike, and by message, such as message content, semantics or sentiment),and other functions. Processed inbound messages are also sent by themessage processor 214 to a message storage module 218 for storage in amessage datastore 220, which stores a permanent message record, whichmessages.

Inbound messages that are not processed by the message processor 214 canbe sent to a chat aggregator 222 for aggregation, recordation andpersistence in a chat datastore 224. These inbound messages can becombined with outbound messages based on their being part of an ongoing“chat” or dialog of related messages or messaging threads.

The event bus and message broker 202 further includes an outboundmessages module 226 that receives client messages from a client userinterface (UI), such as is provided by a messaging application on theclient device, or from a dashboard provided by the messaging platform,and via client messages processor 230. The client messages processor 230checks outbound messages from the client to the users against the userdetail datastore 212 to ensure each targeted user is registered and/oractive with the system 200, or to assist in modifying, curating,filtering or other processing of outbound messages, such as adding textto the message, modifying or augmenting a message based on user behavioror demographics, or the like. As with the inbound messages module 204,the outbound messages module 226 can send some or all of the outboundmessages to the chat aggregator 222 for aggregation, recordation andpersistence in the chat datastore 224. The outbound messages module 226also sends outbound messages to the message storage module 218 forstorage in the message datastore 220, and for dispatch to theintercarrier vendors 201.

Outbound messages from a client define an event, which can be furtherprocessed by user event processor 232 if related to one or more users,or client event processor 234 if related to the client. Events are sentto an event archive for storage in an event datastore 238.

In some implementations, the system 200 is configured with a module forchurn predicting, i.e. a modeling system for predicting churn or apropensity of a user to drop out of the messaging platform. The goal ofthe modeling system is to optimize engagement by users with the clients.In some cases, the system can employ natural language processing toascertain a mood or engagement of a user. In other cases, the system canautomatically generate a “suggestion card” message soliciting input fromone or more users that have exhibited some kind of targeted behavior oreven mood.

Audience Platform for Messaging

When sending a message to a large audience or large group of users, theaudience can be defined from a larger pool of potential recipients basedon information known about them. For example, a client wants to send atext message to all Spanish-speaking women in the Miami area that arepart of a list of potential recipients. The target audience can besegment by name, gender, age, geography, and/or previous communicationswith user recipients (i.e. did a user reply to the client in the lastweek, or are there any recognizable patterns), along with anything elsethat can be discerned from the use history, including topics that theyare interested in (ex: if a user sends # Iowa, or # human trafficking,the system can quickly understand the user's affinities of aspects of aclient's life or existence to develop and direct, or target, users withspecific message content).

Users can be counted and/or tracked for gamification purposes. Forinstance, each client can display their number of users and/or activeengagement thereof. Users can be filtered or prioritized by their joindate, i.e. the date of which they officially joined in the service. Eachuser can be tracked for their engagement or participation on the system.For instance, the system can track each user's number of messages,particularly as related to responses to messages sent or broadcast byclients to many different users. The system can be configured togenerate a queue of messages to be sent to each of the number of users,and the queue can be prioritized so as to be segmented for optimaltransmission according to, among other variables, carrier constraints,message channel bandwidth, local time of a recipient, or othervariables.

The system can be configured to track responses per message from aclient, responses per conversation (i.e. a collection of messages in acommon messaging thread), as well as other user metrics, such asresponse rate, message context as related to response rate, and othermetrics.

In some implementations, a system can include a digital rightsmanagement (DRM) module to track and manage digital contentdistribution. Such DRM module can be integrated with customerrelationship management (CRM) system so as to leverage user engagementwith the clients, to generate reports and campaigns for various itemssuch as merchandising, content distribution, or viral distribution ofgroups among users that are related in some way, either by interest ordemographics, or otherwise.

The system can be configured to define one or more events related tomessaging by the client to their users. In these instances, the systemcan define a time or time period in which messages will be generated andsent, and this time or time period can also be broadcast to the userbase, as well as others, to generate interest and interaction by theusers with the client. The client can either manually control suchevents, or the events can be automatically by the system using ML or AIalgorithms.

In some implementations, the system can include a translator totranslate messages from an original language into a different language.The translation can be automatic, and can occur bi-directionally, i.e.from client to user(s) or from user(s) to client.

Natural language processing can be used by the system to determine oneor more parameters of the messages, such as, without limitation, messagestart, conversation end, new conversation, message context, dynamiccontextual relationships, etc. Further, the natural language processingcan be used by the system to generate new messages on behalf of theclient, which closely track and mimic a client's tone, idioms, axioms,and other personality-specific traits related to the client.

FIG. 3 depicts a user interface or dashboard 300, in which a client canview and manage inbound and outbound messages, view the users associatedwith each outbound message, and view responses from the users. In someinstances, only a subset of users will respond, and accordingly, thedashboard 300 can include a window to track user actions and reactions,so as to view sentiment, engagement, or the like. FIG. 4 depicts a userinterface or dashboard 400 that allows a client to track user actionsand reactions on their client device such as a mobile phone or tabletcomputer, for example. As depicted in FIG. 5, the messaging platform canalso provide a client dashboard 500 for grouping users into one or more“communities,” in which users are grouped based on their interests, theregistration to the community, their demographics or other groupings.Each community can be selected to display activity history or trendingactions. The history or trends can be displayed according to user, timeof receipt, or other display preference by the client.

FIG. 6 is a flowchart of a method 600 for grouping responses in aone-to-many messaging platform. At 602, response text messages arereceived by a messaging platform from a corresponding number of users inresponse to a first text message from a client. The response textmessages can number between 2 and perhaps many millions or more. Thefirst text message and the response text messages are transmitted viaone or more messaging services that interface with the messagingplatform. At 604, a computer processor associated with the messagingplatform executes instructions to analyze one or more attributesassociated with each of the response text messages. At 606, the computerprocessor generates metadata for each of the plurality of response textmessages. The metadata represents the one or more attributes associatedwith each of the response text messages or a user associated withselected ones of each of the response text messages. At 608, thecomputer processor stores the metadata for each of the response textmessages in a database. The storing at 608 further including linking themetadata with the content of each of the response text messages, so asto effectively group the responses messages for functions such asassessing reactions, user actions, semantics, sentiment, or the like.

FIG. 7 is a flowchart of a method 700 for determining sentiment and/orsemantics of responses in a one-to-many messaging platform.communicating, At 702, one or more text messages are communicatedbetween a client and a number of users, via one or more messagingservices that interface with a messaging platform. At 704, the messagingplatform receives user text messages from individual ones of theplurality of users via the one or more messaging services. At 706, amachine learning module of the messaging platform executes one or moreartificial intelligence algorithms on the received user text messages,and at 708, processes the user text messages according to the artificialintelligence algorithms. At 710, based on one or more of variablesassociated with the processed user text messages, metadata is generatedfor each of the user text messages. The metadata represents one or moreattributes associated with content of each of the plurality of user textmessages or a user associated with the user text messages. Theattributes can include sentiment, semantic meaning, or can representuser action or reaction.

FIG. 8 is a flowchart of a method 800 for segmenting users of aone-to-many messaging platform. At 802 a messaging platform receives afirst text message from a client via a first messaging service thatinterfaces with the messaging platform. The first text message isconfigured for transmission via one or more second messaging services touser devices corresponding with a number of users. Each of the usersbeing are registered with the messaging platform and associated with theclient via the messaging platform. For instance, each user can beassociated to a common group or “community” of users, around a commontrait or interest. At 804, the messaging platform segments the usersaccording to one or more user segments. Each of the one or more usersegments can be based on one or more user attributes associated with theusers. The attributes can be defined by static metadata that isgenerated when each user is registered with the messaging platform,and/or by dynamic information about user behavior using the messagingplatform and/or the one or more second messaging services. At 806, themessaging platform customizes the first text message into a set of oneor more second text messages. The customizing is based on thesegmenting, and provides a context to each of the set of second textmessages, where the context corresponds to the one or more userattributes. At 808, the messaging platform transmits, via the one ormore second messaging services, the set of second text messages to theuser devices associated with each of at least some of the users.

FIG. 9 is a flowchart of a method for multivariate testing of messagesto a subgroup in a one-to-many messaging platform. At 902, a messagingplatform generates a text message associated with a client, the messagebeing generated for transmission to a plurality of users via one or moremessaging services. At 904, the messaging platform defines a subset ofthe plurality of users, the subset being defined according to one ormore attributes associated with the text message and/or the plurality ofusers. At 906, the messaging platform transmits the text message to thesubset of the plurality of users via at least one of the one or moremessaging services. At 908, the messaging platform analyzes one or morevariables of the transmitting of the text message to the subset of theplurality of users, the analyzing generating performance metrics of thetext message relative to the subset of the plurality of users. At 910,the messaging platform optimizes the text message based on theperformance metrics generated from the analyzing. At 912, the messagingplatform configures the optimized text message for transmission to theplurality of users or other subsets of the plurality of users via theone or more messaging services.

One or more aspects or features of the subject matter described hereincan be realized in digital electronic circuitry, integrated circuitry,specially designed application specific integrated circuits (ASICs),field programmable gate arrays (FPGAs) computer hardware, firmware,software, and/or combinations thereof. These various aspects or featurescan include implementation in one or more computer programs that areexecutable and/or interpretable on a programmable system including atleast one programmable processor, which can be special or generalpurpose, coupled to receive data and instructions from, and to transmitdata and instructions to, a storage system, at least one input device,and at least one output device. The programmable system or computingsystem may include clients and servers. A client and server aregenerally remote from each other and typically interact through acommunication network. The relationship of client and server arises byvirtue of computer programs running on the respective computers andhaving a client-server relationship to each other.

These computer programs, which can also be referred to programs,software, software applications, applications, components, or code,include machine instructions for a programmable processor, and can beimplemented in a high-level procedural language, an object-orientedprogramming language, a functional programming language, a logicalprogramming language, and/or in assembly/machine language. As usedherein, the term “machine-readable medium” refers to any computerprogram product, apparatus and/or device, such as for example magneticdiscs, optical disks, memory, and Programmable Logic Devices (PLDs),used to provide machine instructions and/or data to a programmableprocessor, including a machine-readable medium that receives machineinstructions as a machine-readable signal. The term “machine-readablesignal” refers to any signal used to provide machine instructions and/ordata to a programmable processor. The machine-readable medium can storesuch machine instructions non-transitorily, such as for example as woulda non-transient solid-state memory or a magnetic hard drive or anyequivalent storage medium. The machine-readable medium can alternativelyor additionally store such machine instructions in a transient manner,such as for example as would a processor cache or other random accessmemory associated with one or more physical processor cores.

To provide for interaction with a user, one or more aspects or featuresof the subject matter described herein can be implemented on a computerhaving a display device, such as for example a cathode ray tube (CRT) ora liquid crystal display (LCD) or a light emitting diode (LED) monitorfor displaying information to the user and a keyboard and a pointingdevice, such as for example a mouse or a trackball, by which the usermay provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. For example, feedbackprovided to the user can be any form of sensory feedback, such as forexample visual feedback, auditory feedback, or tactile feedback; andinput from the user may be received in any form, including, but notlimited to, acoustic, speech, or tactile input. Other possible inputdevices include, but are not limited to, touch screens or othertouch-sensitive devices such as single or multi-point resistive orcapacitive trackpads, voice recognition hardware and software, opticalscanners, optical pointers, digital image capture devices and associatedinterpretation software, and the like.

In the descriptions above and in the claims, phrases such as “at leastone of” or “one or more of” may occur followed by a conjunctive list ofelements or features. The term “and/or” may also occur in a list of twoor more elements or features. Unless otherwise implicitly or explicitlycontradicted by the context in which it used, such a phrase is intendedto mean any of the listed elements or features individually or any ofthe recited elements or features in combination with any of the otherrecited elements or features. For example, the phrases “at least one ofA and B;” “one or more of A and B;” and “A and/or B” are each intendedto mean “A alone, B alone, or A and B together.” A similarinterpretation is also intended for lists including three or more items.For example, the phrases “at least one of A, B, and C;” “one or more ofA, B, and C;” and “A, B, and/or C” are each intended to mean “A alone, Balone, C alone, A and B together, A and C together, B and C together, orA and B and C together.” Use of the term “based on,” above and in theclaims is intended to mean, “based at least in part on,” such that anunrecited feature or element is also permissible.

The subject matter described herein can be embodied in systems,apparatus, methods, and/or articles depending on the desiredconfiguration. The implementations set forth in the foregoingdescription do not represent all implementations consistent with thesubject matter described herein. Instead, they are merely some examplesconsistent with aspects related to the described subject matter.Although a few variations have been described in detail above, othermodifications or additions are possible. In particular, further featuresand/or variations can be provided in addition to those set forth herein.For example, the implementations described above can be directed tovarious combinations and subcombinations of the disclosed featuresand/or combinations and subcombinations of several further featuresdisclosed above. In addition, the logic flows depicted in theaccompanying figures and/or described herein do not necessarily requirethe particular order shown, or sequential order, to achieve desirableresults. Other implementations may be within the scope of the followingclaims.

What is claimed is:
 1. A method comprising: generating, by a messagingplatform, a text message associated with a client, the message beinggenerated for transmission to a plurality of users via one or moremessaging services; defining, by the messaging platform, a subset of theplurality of users, the subset being defined according to one or moreattributes associated with the text message and/or the plurality ofusers; transmitting, by the messaging platform and via at least one ofthe one or more messaging services, the text message to the subset ofthe plurality of users; analyzing, by the messaging platform, one ormore variables of the transmitting of the text message to the subset ofthe plurality of users, the analyzing generating performance metrics ofthe text message relative to the subset of the plurality of users;optimizing, by the messaging platform, the text message based on theperformance metrics generated from the analyzing; and configuring, bythe messaging platform, the optimized text message for transmission tothe plurality of users or other subsets of the plurality of users viathe one or more messaging services.
 2. A method in accordance with claim1, wherein the one or more attributes associated with the text messageand/or the plurality of users include user demographics of the pluralityof users.
 3. A method in accordance with claim 1, wherein theperformance metrics includes an appropriateness score based on a contextof the text message,
 4. A method in accordance with claim 3, wherein theappropriateness score is generated based on one or more reply messagesfrom at least one of the subset of the plurality of users.
 5. A methodin accordance with claim 4, further comprising analyzing, by themessaging platform, the one or more reply messages for a context of eachof the one or more reply messages, the appropriateness score comprisinga mapping of the context of the text message to the context of each ofthe one or more reply messages.
 6. A method in accordance with claim 1,wherein each of the plurality of users is a registrant of the messagingplatform.
 7. A method in accordance with claim 1, wherein the othersubsets of the plurality of users is defined at least partiallyaccording to a machine learning or artificial intelligence algorithm. 8.A messaging platform having a computer program product comprising anon-transitory machine-readable medium storing instructions that, whenexecuted by at least one programmable processor, cause the at least oneprogrammable processor to perform operations comprising: generate a textmessage associated with a client, the message being generated fortransmission to a plurality of users via one or more messaging services;define a subset of the plurality of users, the subset being definedaccording to one or more attributes associated with the text messageand/or the plurality of users; transmit via at least one of the one ormore messaging services, the text message to the subset of the pluralityof users; analyze one or more variables of the transmitting of the textmessage to the subset of the plurality of users, the analyze operationgenerating performance metrics of the text message relative to thesubset of the plurality of users; optimize the text message based on theperformance metrics generated from the analyze operation; and configurethe optimized text message for transmission to the plurality of users orother subsets of the plurality of users via the one or more messagingservices.
 9. The messaging platform in accordance with claim 8, whereinthe one or more attributes associated with the text message and/or theplurality of users include user demographics of the plurality of users.10. The messaging platform in accordance with claim 8, wherein theperformance metrics includes an appropriateness score based on a contextof the text message,
 11. The messaging platform in accordance with claim10, wherein the appropriateness score is generated based on one or morereply messages from at least one of the subset of the plurality ofusers.
 12. The messaging platform in accordance with claim 11, whereinthe operations further comprise an operation to analyze the one or morereply messages for a context of each of the one or more reply messages,the appropriateness score comprising a mapping of the context of thetext message to the context of each of the one or more reply messages.13. The messaging platform in accordance with claim 8, wherein each ofthe plurality of users is a registrant of the messaging platform. 14.The messaging platform in accordance with claim 8, wherein the othersubsets of the plurality of users is defined at least partiallyaccording to a machine learning or artificial intelligence algorithm.15. A system comprising: a messaging platform that facilitatescommunication between one or more clients and a plurality of users viaone or more messaging services used by user devices associated with theone or more clients and the plurality of users, each of the plurality ofusers being registered with the messaging platform and associated withat least one of the one or more clients via the messaging platform; aprogrammable processor in communication with the messaging platform; anda machine-readable medium storing instructions that, when executed bythe programmable processor, cause the at least one programmableprocessor to perform operations comprising: generate a text messageassociated with a client, the message being generated for transmissionto a plurality of users via one or more messaging services; define asubset of the plurality of users, the subset being defined according toone or more attributes associated with the text message and/or theplurality of users; transmit via at least one of the one or moremessaging services, the text message to the subset of the plurality ofusers; analyze one or more variables of the transmitting of the textmessage to the subset of the plurality of users, the analyze operationgenerating performance metrics of the text message relative to thesubset of the plurality of users; optimize the text message based on theperformance metrics generated from the analyze operation; and configurethe optimized text message for transmission to the plurality of users orother subsets of the plurality of users via the one or more messagingservices.
 16. The messaging platform in accordance with claim 15,wherein the one or more attributes associated with the text messageand/or the plurality of users include user demographics of the pluralityof users.
 17. The messaging platform in accordance with claim 15,wherein the performance metrics includes an appropriateness score basedon a context of the text message,
 18. The messaging platform inaccordance with claim 17, wherein the appropriateness score is generatedbased on one or more reply messages from at least one of the subset ofthe plurality of users.
 19. The messaging platform in accordance withclaim 18, wherein the operations further comprise an operation toanalyze the one or more reply messages for a context of each of the oneor more reply messages, the appropriateness score comprising a mappingof the context of the text message to the context of each of the one ormore reply messages.
 20. The messaging platform in accordance with claim15, wherein each of the plurality of users is a registrant of themessaging platform.
 21. The messaging platform in accordance with claim15, wherein the other subsets of the plurality of users is defined atleast partially according to a machine learning or artificialintelligence algorithm.